Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approach
Main Author: | |
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Publication Date: | 2020 |
Other Authors: | , , , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10400.21/12700 |
Summary: | The power electronic converter design is essential for the operation of the switched reluctance motor (SRM). Thus, a fault-tolerant power converter is fundamental to ensure high reliability and extend the drive operation. To achieve fault tolerance, fault detection and diagnosis methods are critical in order to identify, as soon as possible, the failure mode of the drive. To provide such capability, it is proposed in this paper a new fault-tolerant power converter scheme combined with a fault detection method regarding the most common power semiconductors failures in SRM drives. The fast and reliable proposed diagnosis method is based on the entropy theory. Based on this theory, normalized indexes (diagnostic variables) are created, which are independent from the load and speed of the motor. Through this method, it is possible to identify the faulty leg, as well as the type of power semiconductor fault. To test and evaluate the proposed solution several laboratory experiments were carried out using a 2 kW four-phase 8 / 6 SRM. |
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Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approachSwitched reluctance motor (SRM)Motor drivesFault-tolerantFault detectionFault diagnosisEntropy-based featureThe power electronic converter design is essential for the operation of the switched reluctance motor (SRM). Thus, a fault-tolerant power converter is fundamental to ensure high reliability and extend the drive operation. To achieve fault tolerance, fault detection and diagnosis methods are critical in order to identify, as soon as possible, the failure mode of the drive. To provide such capability, it is proposed in this paper a new fault-tolerant power converter scheme combined with a fault detection method regarding the most common power semiconductors failures in SRM drives. The fast and reliable proposed diagnosis method is based on the entropy theory. Based on this theory, normalized indexes (diagnostic variables) are created, which are independent from the load and speed of the motor. Through this method, it is possible to identify the faulty leg, as well as the type of power semiconductor fault. To test and evaluate the proposed solution several laboratory experiments were carried out using a 2 kW four-phase 8 / 6 SRM.MDPIRCIPLFernao Pires, VitorAmaral, TitoCordeiro, ArmandoFoito, DanielPires, Armando J.Martins, Joao2021-01-26T13:49:10Z2020-05-192020-05-19T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/12700eng10.3390/app10103516info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-12T07:20:38Zoai:repositorio.ipl.pt:10400.21/12700Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:49:00.013924Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approach |
title |
Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approach |
spellingShingle |
Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approach Fernao Pires, Vitor Switched reluctance motor (SRM) Motor drives Fault-tolerant Fault detection Fault diagnosis Entropy-based feature |
title_short |
Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approach |
title_full |
Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approach |
title_fullStr |
Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approach |
title_full_unstemmed |
Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approach |
title_sort |
Fault-tolerant SRM dive with a diagnosis method based on the entropy feature approach |
author |
Fernao Pires, Vitor |
author_facet |
Fernao Pires, Vitor Amaral, Tito Cordeiro, Armando Foito, Daniel Pires, Armando J. Martins, Joao |
author_role |
author |
author2 |
Amaral, Tito Cordeiro, Armando Foito, Daniel Pires, Armando J. Martins, Joao |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Fernao Pires, Vitor Amaral, Tito Cordeiro, Armando Foito, Daniel Pires, Armando J. Martins, Joao |
dc.subject.por.fl_str_mv |
Switched reluctance motor (SRM) Motor drives Fault-tolerant Fault detection Fault diagnosis Entropy-based feature |
topic |
Switched reluctance motor (SRM) Motor drives Fault-tolerant Fault detection Fault diagnosis Entropy-based feature |
description |
The power electronic converter design is essential for the operation of the switched reluctance motor (SRM). Thus, a fault-tolerant power converter is fundamental to ensure high reliability and extend the drive operation. To achieve fault tolerance, fault detection and diagnosis methods are critical in order to identify, as soon as possible, the failure mode of the drive. To provide such capability, it is proposed in this paper a new fault-tolerant power converter scheme combined with a fault detection method regarding the most common power semiconductors failures in SRM drives. The fast and reliable proposed diagnosis method is based on the entropy theory. Based on this theory, normalized indexes (diagnostic variables) are created, which are independent from the load and speed of the motor. Through this method, it is possible to identify the faulty leg, as well as the type of power semiconductor fault. To test and evaluate the proposed solution several laboratory experiments were carried out using a 2 kW four-phase 8 / 6 SRM. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-05-19 2020-05-19T00:00:00Z 2021-01-26T13:49:10Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.21/12700 |
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http://hdl.handle.net/10400.21/12700 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.3390/app10103516 |
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openAccess |
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MDPI |
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